Manage project-level alignment and context for AI agent workflows in the Ravi runtime.
npx skills add https://github.com/filipexyz/ravi --skill projects-filipexyz
Please help me install this Agent Skill. Skill: projects Source: https://github.com/filipexyz/ravi/tree/main/src/plugins/internal/ravi-system/skills/projects Command: npx skills add https://github.com/filipexyz/ravi --skill projects-filipexyz
This skill solves the fragmentation of context in long-lived AI agent operations by providing a structured alignment layer that links workflows, tasks, and resources without creating rigid, monolithic project management overhead.
Use the projects skill to initialize a new project named Ravi System with the slug ravi-system and set the owner agent to dev.
High-intent search queries and answers about installing and using this skill.
To manage AI agent workflows and maintain context across long-lived tasks, you can use a structured alignment layer that links workflows, tasks, and resources together. This prevents context fragmentation without introducing rigid project management overhead.
You can link repositories and external documentation to an AI agent project through resource management features. These allow easy linking of worktrees, repositories, and external docs to keep necessary assets within the agent's reach.
Yes, you need the Ravi CLI environment to track project workflows and tasks. The system requires the Ravi CLI to execute mutations and state updates across the agent's session lifecycle.
To initialize a new project in Ravi, you use the projects skill to create a project name and slug, then set the owner agent. For example, you can create a project named Ravi System with the slug ravi-system and set the owner to dev.
The best way to align workflow runs with a specific AI agent project is through workflow coordination features. These enable the initiation and attachment of workflow runs directly to specific projects to maintain operational focus.
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